B2B companies today rely on Configure-Price-Quote (CPQ) solutions to sell complex products and services. Platforms like Logik.ai (now part of ServiceNow), Salesforce CPQ, Oracle CPQ, and SAP CPQ promise faster quotes and fewer errors. Yet many organizations still struggle with CPQ project delivery.
We’ll explore four real-world challenges that slow down CPQ implementations and daily operations – and why modern approaches are emerging to tackle them. We’ll focus on data and examples from Manufacturing, High Tech, and Health & Life Sciences, and consider how Logik.ai’s integration with ServiceNow can help overcome these hurdles.
Major challenges include:
- Shortage of CPQ-Skilled Talent – Limited availability of experienced CPQ implementers in the U.S. and globally. → See our previous blog
Today’s focus:
- Outdated, Manual Delivery Processes – Legacy quoting methods and processes that drag out releases and hurt the business.
- Fragmented Tooling and Siloed Implementation – Lack of standardized, scalable toolkits in the CPQ ecosystem, leading to inefficiencies.
Up Next:
- Unstructured Configuration Data Stifling AI – Difficulty applying AI/automation because product and pricing data are not properly structured.
Each of these pain points can derail a CPQ initiative. This post focuses on challenges 2 & 3 above.
2. Outdated & Manual Processes Slow Everything Down
Many B2B organizations continue to depend on legacy quoting workflows that were designed for slower, less interconnected sales cycles. These manual methods—often centered around spreadsheets, tribal knowledge, and disconnected tools—fail to meet the demands of today’s complex, fast-paced selling environments. According to a Forrester study, 52% of B2B buyers say they are frustrated by inconsistent or slow quoting processes, citing a lack of automation as a major barrier to closing deals efficiently.
A key issue is the absence of integrated automation between core systems like CRM, ERP, and CPQ. Without real-time data synchronization, teams resort to manual data entry, increasing the risk of errors and elongating quote cycles. In industries like High Tech and Life Sciences, where sales cycles are compressed and product variations are significant, this inefficiency can be a deal-breaker. Gartner’s Market Guide for Configure, Price and Quote Applications highlights this as a leading reason why CPQ projects fail to deliver ROI.
Change Management
Rigid change management compounds the problem. Traditional CPQ setups often require custom code or IT-intensive deployments to update pricing logic, configuration rules, or discount thresholds. This slows time-to-market and reduces flexibility when responding to new market conditions, such as supply chain disruptions or regulatory shifts—issues that are especially common in Manufacturing. Modern platforms with low-code/no-code capabilities are rapidly changing this, enabling faster iteration and lower total cost of ownership.
Furthermore, without robust business rules and automated guardrails, outdated delivery processes open the door to quote inaccuracies and revenue leakage. According to McKinsey, companies without strong CPQ controls experience up to 5% in lost margins due to inconsistent discounting and misconfigured orders.
Modern CPQ
Modern CPQ systems like Logik.ai’s integration with ServiceNow help address these issues by offering flexible, scalable configuration engines with built-in testing environments and real-time analytics. This enables rapid deployment of quoting changes and improves cross-team collaboration without the drag of legacy infrastructure.
Why It Matters
When delivery processes are manual and inflexible, the cost is more than just internal frustration. It leads to lost deals, slower revenue cycles, and damaged customer trust. For sales teams, every minute waiting on IT to deploy a rule change or reprocess an incorrect quote is a lost opportunity. For leadership, outdated CPQ systems reduce visibility into pipeline accuracy and quote profitability, making it harder to forecast and scale.
By transitioning to modern, agile delivery models, B2B organizations can dramatically reduce quote turnaround time, ensure compliance, and adapt to market changes in real time. In a landscape where speed and accuracy are critical differentiators, upgrading legacy CPQ delivery is not just a technology investment—it’s a strategic imperative.
3. Fragmented Tooling and Lack of Standardization
Another challenge in the CPQ world is the fragmentation of tooling used to implement and maintain these systems. Unlike core software development, which has mature, standardized DevOps toolchains, CPQ implementation often feels like reinventing the wheel for each platform or project. Different CPQ software (Salesforce vs. Oracle vs. SAP) have entirely different configuration mechanisms, and even within one platform, teams end up using ad-hoc solutions to fill gaps. This lack of a standardized, scalable toolkit slows delivery and complicates maintenance.
A prime example is deploying configuration changes for Salesforce CPQ (formerly SteelBrick). Salesforce CPQ stores many of its product rules, pricing rules, and templates as data records rather than metadata. This means you cannot simply include those changes in a normal deployment pipeline (change sets or CI/CD).
As one CPQ developer lamented,
The CPQ package is “built on individual records that can’t be added to [Salesforce’s] standard outbound change set process”, so pushing updates requires an additional tool or manual data load.
In practice, teams often resort to Excel or CSV exports and the Data Loader to migrate CPQ data between orgs – a tedious and error-prone workaround. It’s common to spend hours mapping objects and moving CPQ data from a sandbox to production, since the platform’s native tools don’t support it.
Beyond Deployment Issues
Mistakes in this process lead to do-overs, further slowing down releases. Beyond deployment issues, there’s fragmentation in how CPQ rules and processes are designed. Each implementation partner might have their own proprietary spreadsheet templates or scripting hacks to manage large product catalogs. There is no universal “CPQ toolkit” that everyone uses, unlike, say, how web developers universally use Git and code frameworks. This means lessons learned aren’t easily transferred across platforms or projects.
A team implementing Oracle CPQ might struggle with a lack of robust version control or testing tools, while a team on SAP CPQ wrestles with a different set of quirks. The overall ecosystem lacks consistent, scalable methods to build and test CPQ configurations. Even tasks like debugging can be cumbersome: for instance, standard automation and CI tools often don’t integrate smoothly with CPQ logic. One engineer pointed out that due to limited debugging insight from CPQ packages, “a developer only has a theory as to how CPQ will interact with [Salesforce] Apex, Flow or any other standard process,” making it hard to troubleshoot and optimize.
Why it matters
Fragmented tooling leads to siloed efforts and higher maintenance overhead. When each CPQ update requires manual processes or separate third-party tools, release cycles slow down and the risk of errors increases. It’s also a scalability issue – you can’t easily template and reproduce a CPQ rollout for another business unit or geography if everything is done in a bespoke way the first time. For companies operating in multiple regions or merging after acquisitions, this lack of standardization in CPQ can be a major headache. It also ties back to the talent issue: if only a few people know the quirky tool or method your CPQ uses, it’s hard to scale out the team. In summary, fragmented tooling keeps CPQ projects from achieving the same velocity and reliability that we expect from modern software delivery, often resulting in slower time-to-value for the CPQ investment.
Now Is the Time to Modernize CPQ
Legacy CPQ systems are often defined by manual processes, siloed tools, and slow delivery cycles, hindering growth and agility in B2B sales. Logik.ai and ServiceNow offer a modern alternative: a unified, scalable approach that combines powerful configuration with workflow-driven automation.
By streamlining rule management, enabling low-code updates, and supporting real-time deployment, Logik.ai’s engine on the ServiceNow platform empowers teams to deliver faster, more accurate quotes at scale. The result is a CPQ strategy built not just for today’s complexity, but for tomorrow’s growth.
Ready to modernize your CPQ approach? Speak with Zaelab’s experts to explore how your organization can overcome these challenges and accelerate time-to-value.
